Enhancing diffuse correlation spectroscopy pulsatile cerebral blood flow signal with near-infrared spectroscopy...

Combining near-infrared spectroscopy (NIRS) and diffuse correlation spectroscopy (DCS) allows for quantifying cerebral blood volume, flow, and oxygenation changes continuously and non-invasively. As recently shown, the DCS pulsatile cerebral blood flow index (${\mathrm{pCBF}}_i$) can be used to quantify critical closing pressure (CrCP) and cerebrovascular resistance (${\mathrm{CVR}}_i$).

Although current DCS technology allows for reliable monitoring of the slow hemodynamic changes, resolving pulsatile blood flow at large source-detector separations, which is needed to ensure cerebral sensitivity, is challenging because of its low signal-to-noise ratio (SNR). Cardiac-gated averaging of several arterial pulse cycles is required to obtain a meaningful waveform.

Taking advantage of the high SNR of NIRS, we demonstrate a method that uses the NIRS photoplethysmography (NIRS-PPG) pulsatile signal to model DCS ${\mathrm{pCBF}}_i$, reducing the coefficient of variation of the recovered pulsatile waveform (${\mathrm{pCBF}}_{i\text{-}\text{fit}}$) and allowing for an unprecedented temporal resolution (266 Hz) at a large source-detector separation ($>3\mathrm{cm}$).

In 10 healthy subjects, we verified the quality of the NIRS-PPG ${\mathrm{pCBF}}_{i\text{-}\text{fit}}$ during common tasks, showing high fidelity against ${\mathrm{pCBF}}_i$ ($R^2$ $0.98\pm 0.01$). We recovered CrCP and ${\mathrm{CVR}}_i$ at 0.25 Hz, $>10$ times faster than previously achieved with DCS.

NIRS-PPG improves DCS ${\mathrm{pCBF}}_i$ SNR, reducing the number of gate-averaged heartbeats required to recover CrCP and ${\mathrm{CVR}}_i$.